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Predictors without (much) variance do not add to the model. Better exclude them, at least know them.
The variables with near zero variance are Dystymia, Agoraphobia, SeparationAnx, PTSD, ODD, EatingDis.
Scale quality involves aspects as intercorrelation of items of a scale, internal consisteny, score distribution, and the like. Let’s see.
Let’s check the distribution for the sum scores variables (which are: CYBOCS_pre_sum, ChOCI_R_C_sumsym_PRE, ChOCI_R_C_sumimp_PRE, EWSASC_sum_PRE, SCAS_S_C_sum_PRE, CDI_S_sum_PRE, ChOCI_R_P_sumsym_PRE, ChOCI_R_P_sumimp_PRE, FAS_PR_sum_PRE, EWSASP_sum_PRE, SCAS_S_P_sum_PRE, responder_3m_f, CYBOCS_3m.
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If one suffers from one comorbidity, does he/she suffer (in general) from other comorbidities too? NZV variables are excluded.
We should do this more stringently, but let’s start with a brief look to the items of ChOCI, to see whether they are correlated (as they should be, at least for common subscale-items). Those are quite a few.
##
## Reliability analysis
## Call: psych::alpha(x = data.frame(ChOCI_items), check.keys = TRUE)
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd
## 0.87 0.87 0.95 0.17 6.8 0.024 1.2 0.38
##
## lower alpha upper 95% confidence boundaries
## 0.82 0.87 0.91
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N alpha se
## ChOCI_R_C_1_PRE 0.86 0.87 0.95 0.17 6.5 0.024
## ChOCI_R_C_2_PRE 0.87 0.87 0.95 0.18 6.8 0.024
## ChOCI_R_C_3_PRE 0.86 0.87 0.95 0.17 6.5 0.024
## ChOCI_R_C_4_PRE 0.86 0.87 0.95 0.18 6.6 0.024
## ChOCI_R_C_5_PRE 0.87 0.87 0.95 0.18 7.0 0.023
## ChOCI_R_C_6_PRE 0.87 0.87 0.95 0.18 6.7 0.024
## ChOCI_R_C_7_PRE 0.86 0.87 0.95 0.17 6.5 0.024
## ChOCI_R_C_8_PRE 0.87 0.87 0.95 0.18 6.7 0.023
## ChOCI_R_C_9_PRE 0.87 0.87 0.95 0.18 6.7 0.024
## ChOCI_R_C_10_PRE 0.86 0.87 0.95 0.17 6.4 0.025
## ChOCI_R_C_12_PRE 0.86 0.86 0.95 0.17 6.3 0.026
## ChOCI_R_C_13_PRE 0.85 0.86 0.95 0.17 6.2 0.026
## ChOCI_R_C_14_PRE 0.86 0.87 0.95 0.17 6.5 0.025
## ChOCI_R_C_15_PRE 0.87 0.87 0.95 0.18 6.9 0.023
## ChOCI_R_C_16_PRE 0.86 0.86 0.95 0.17 6.4 0.025
## ChOCI_R_C_17_PRE 0.86 0.87 0.95 0.17 6.4 0.025
## ChOCI_R_C_18_PRE 0.86 0.87 0.95 0.17 6.5 0.024
## ChOCI_R_C_19_PRE 0.86 0.87 0.95 0.17 6.4 0.024
## ChOCI_R_C_20_PRE 0.86 0.86 0.95 0.17 6.3 0.025
## ChOCI_R_C_21_PRE 0.86 0.87 0.95 0.18 6.6 0.024
## ChOCI_R_C_22_PRE 0.86 0.86 0.95 0.17 6.4 0.024
## ChOCI_R_C_23_PRE 0.86 0.87 0.95 0.17 6.5 0.024
## ChOCI_R_C_24_PRE 0.86 0.87 0.95 0.17 6.5 0.024
## ChOCI_R_C_25_PRE 0.86 0.87 0.95 0.17 6.5 0.024
## ChOCI_R_C_26_PRE 0.87 0.87 0.96 0.18 7.0 0.023
## ChOCI_R_C_27_PRE 0.86 0.86 0.95 0.17 6.3 0.024
## ChOCI_R_C_29_PRE 0.86 0.87 0.95 0.17 6.5 0.024
## ChOCI_R_C_30_PRE 0.86 0.86 0.95 0.17 6.4 0.025
## ChOCI_R_C_31_PRE 0.86 0.86 0.95 0.17 6.4 0.025
## ChOCI_R_C_32_PRE- 0.87 0.87 0.95 0.18 7.0 0.023
## ChOCI_R_C_33_PRE 0.86 0.87 0.95 0.18 6.6 0.024
## ChOCI_R_C_34_PRE 0.86 0.87 0.95 0.17 6.5 0.025
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## ChOCI_R_C_1_PRE 61 0.454 0.46 0.45 0.392 1.03 0.89
## ChOCI_R_C_2_PRE 61 0.300 0.30 0.29 0.238 0.82 0.81
## ChOCI_R_C_3_PRE 61 0.446 0.45 0.44 0.395 1.16 0.73
## ChOCI_R_C_4_PRE 61 0.376 0.42 0.41 0.318 1.10 0.79
## ChOCI_R_C_5_PRE 61 0.138 0.16 0.14 0.081 0.61 0.69
## ChOCI_R_C_6_PRE 61 0.326 0.32 0.31 0.259 0.98 0.88
## ChOCI_R_C_7_PRE 61 0.448 0.48 0.47 0.397 0.54 0.74
## ChOCI_R_C_8_PRE 61 0.309 0.35 0.33 0.244 0.69 0.85
## ChOCI_R_C_9_PRE 61 0.335 0.36 0.33 0.282 0.61 0.71
## ChOCI_R_C_10_PRE 61 0.531 0.53 0.53 0.486 0.72 0.73
## ChOCI_R_C_12_PRE 61 0.701 0.65 0.65 0.660 2.08 0.88
## ChOCI_R_C_13_PRE 61 0.724 0.69 0.69 0.670 1.82 1.23
## ChOCI_R_C_14_PRE 61 0.525 0.50 0.50 0.458 2.56 1.04
## ChOCI_R_C_15_PRE 61 0.170 0.17 0.16 0.087 2.18 1.01
## ChOCI_R_C_16_PRE 61 0.606 0.58 0.58 0.559 2.48 0.85
## ChOCI_R_C_17_PRE 61 0.593 0.52 0.52 0.521 1.44 1.23
## ChOCI_R_C_18_PRE 61 0.436 0.50 0.49 0.393 0.43 0.62
## ChOCI_R_C_19_PRE 61 0.483 0.53 0.52 0.437 0.61 0.69
## ChOCI_R_C_20_PRE 61 0.559 0.59 0.58 0.519 0.52 0.67
## ChOCI_R_C_21_PRE 61 0.415 0.41 0.39 0.357 1.07 0.81
## ChOCI_R_C_22_PRE 61 0.518 0.55 0.54 0.474 0.46 0.70
## ChOCI_R_C_23_PRE 61 0.456 0.50 0.48 0.425 0.30 0.46
## ChOCI_R_C_24_PRE 61 0.409 0.45 0.44 0.370 0.26 0.54
## ChOCI_R_C_25_PRE 61 0.431 0.47 0.46 0.374 0.75 0.81
## ChOCI_R_C_26_PRE 61 0.082 0.14 0.11 0.035 0.33 0.57
## ChOCI_R_C_27_PRE 61 0.553 0.61 0.60 0.525 0.26 0.48
## ChOCI_R_C_29_PRE 61 0.507 0.47 0.46 0.439 1.98 1.04
## ChOCI_R_C_30_PRE 61 0.614 0.56 0.56 0.551 1.57 1.13
## ChOCI_R_C_31_PRE 61 0.594 0.58 0.58 0.533 2.54 1.06
## ChOCI_R_C_32_PRE- 61 0.170 0.13 0.11 0.086 2.03 1.03
## ChOCI_R_C_33_PRE 61 0.438 0.41 0.41 0.385 2.51 0.77
## ChOCI_R_C_34_PRE 61 0.540 0.46 0.46 0.468 1.26 1.15
##
## Non missing response frequency for each item
## 0 1 2 3 4 miss
## ChOCI_R_C_1_PRE 0.38 0.21 0.41 0.00 0.00 0
## ChOCI_R_C_2_PRE 0.43 0.33 0.25 0.00 0.00 0
## ChOCI_R_C_3_PRE 0.20 0.44 0.36 0.00 0.00 0
## ChOCI_R_C_4_PRE 0.26 0.38 0.36 0.00 0.00 0
## ChOCI_R_C_5_PRE 0.51 0.38 0.11 0.00 0.00 0
## ChOCI_R_C_6_PRE 0.39 0.23 0.38 0.00 0.00 0
## ChOCI_R_C_7_PRE 0.61 0.25 0.15 0.00 0.00 0
## ChOCI_R_C_8_PRE 0.56 0.20 0.25 0.00 0.00 0
## ChOCI_R_C_9_PRE 0.52 0.34 0.13 0.00 0.00 0
## ChOCI_R_C_10_PRE 0.44 0.39 0.16 0.00 0.00 0
## ChOCI_R_C_12_PRE 0.02 0.21 0.52 0.16 0.08 0
## ChOCI_R_C_13_PRE 0.15 0.31 0.21 0.23 0.10 0
## ChOCI_R_C_14_PRE 0.05 0.11 0.21 0.48 0.15 0
## ChOCI_R_C_15_PRE 0.03 0.23 0.36 0.28 0.10 0
## ChOCI_R_C_16_PRE 0.02 0.11 0.31 0.49 0.07 0
## ChOCI_R_C_17_PRE 0.31 0.23 0.18 0.26 0.02 0
## ChOCI_R_C_18_PRE 0.64 0.30 0.07 0.00 0.00 0
## ChOCI_R_C_19_PRE 0.51 0.38 0.11 0.00 0.00 0
## ChOCI_R_C_20_PRE 0.57 0.33 0.10 0.00 0.00 0
## ChOCI_R_C_21_PRE 0.30 0.34 0.36 0.00 0.00 0
## ChOCI_R_C_22_PRE 0.66 0.23 0.11 0.00 0.00 0
## ChOCI_R_C_23_PRE 0.70 0.30 0.00 0.00 0.00 0
## ChOCI_R_C_24_PRE 0.79 0.16 0.05 0.00 0.00 0
## ChOCI_R_C_25_PRE 0.48 0.30 0.23 0.00 0.00 0
## ChOCI_R_C_26_PRE 0.72 0.23 0.05 0.00 0.00 0
## ChOCI_R_C_27_PRE 0.75 0.23 0.02 0.00 0.00 0
## ChOCI_R_C_29_PRE 0.03 0.34 0.33 0.20 0.10 0
## ChOCI_R_C_30_PRE 0.21 0.26 0.30 0.20 0.03 0
## ChOCI_R_C_31_PRE 0.05 0.11 0.25 0.43 0.16 0
## ChOCI_R_C_32_PRE 0.05 0.31 0.34 0.21 0.08 0
## ChOCI_R_C_33_PRE 0.02 0.05 0.41 0.46 0.07 0
## ChOCI_R_C_34_PRE 0.33 0.30 0.18 0.18 0.02 0
One item was negatively correlated with the scale (ChOCI_R_C_26_PRE-). It should be checked.
##
## Reliability analysis
## Call: psych::alpha(x = data.frame(ChOCI_items_2), check.keys = TRUE)
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd
## 0.85 0.84 0.95 0.14 5.2 0.026 1.3 0.34
##
## lower alpha upper 95% confidence boundaries
## 0.8 0.85 0.9
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N alpha se
## ChOCI_R_P_1_PRE 0.85 0.84 0.94 0.14 5.1 0.026
## ChOCI_R_P_2_PRE 0.85 0.83 0.94 0.14 5.0 0.026
## ChOCI_R_P_3_PRE 0.85 0.84 0.94 0.15 5.3 0.025
## ChOCI_R_P_4_PRE 0.85 0.83 0.94 0.14 5.0 0.026
## ChOCI_R_P_5_PRE 0.85 0.84 0.94 0.14 5.2 0.025
## ChOCI_R_P_6_PRE 0.85 0.83 0.94 0.14 5.0 0.026
## ChOCI_R_P_7_PRE 0.85 0.84 0.95 0.14 5.1 0.026
## ChOCI_R_P_8_PRE 0.85 0.83 0.94 0.14 5.0 0.026
## ChOCI_R_P_9_PRE 0.85 0.84 0.95 0.14 5.2 0.025
## ChOCI_R_P_10_PRE 0.84 0.83 0.94 0.14 4.8 0.027
## ChOCI_R_P_12_PRE 0.84 0.83 0.94 0.13 4.8 0.027
## ChOCI_R_P_13_PRE 0.84 0.83 0.94 0.13 4.8 0.028
## ChOCI_R_P_14_PRE 0.84 0.83 0.94 0.14 4.8 0.028
## ChOCI_R_P_15_PRE 0.85 0.84 0.94 0.14 5.1 0.026
## ChOCI_R_P_16_PRE 0.84 0.83 0.94 0.13 4.8 0.027
## ChOCI_R_P_17_PRE 0.84 0.83 0.94 0.13 4.8 0.028
## ChOCI_R_P_18_PRE 0.85 0.84 0.94 0.14 5.1 0.026
## ChOCI_R_P_19_PRE 0.85 0.83 0.94 0.14 4.9 0.027
## ChOCI_R_P_20_PRE 0.85 0.83 0.94 0.14 5.0 0.026
## ChOCI_R_P_21_PRE 0.85 0.83 0.94 0.14 5.1 0.026
## ChOCI_R_P_22_PRE 0.85 0.84 0.94 0.14 5.1 0.026
## ChOCI_R_P_23_PRE 0.85 0.83 0.94 0.14 5.0 0.026
## ChOCI_R_P_24_PRE 0.85 0.84 0.94 0.14 5.1 0.026
## ChOCI_R_P_25_PRE 0.85 0.84 0.94 0.14 5.2 0.025
## ChOCI_R_P_26_PRE- 0.85 0.85 0.95 0.15 5.5 0.026
## ChOCI_R_P_27_PRE 0.85 0.84 0.95 0.14 5.2 0.026
## ChOCI_R_P_29_PRE 0.84 0.83 0.94 0.14 4.9 0.027
## ChOCI_R_P_30_PRE 0.84 0.83 0.94 0.13 4.7 0.029
## ChOCI_R_P_31_PRE 0.84 0.83 0.94 0.13 4.8 0.028
## ChOCI_R_P_32_PRE 0.85 0.84 0.94 0.14 5.1 0.026
## ChOCI_R_P_33_PRE 0.84 0.83 0.94 0.14 4.9 0.027
## ChOCI_R_P_34_PRE 0.84 0.83 0.94 0.13 4.7 0.029
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## ChOCI_R_P_1_PRE 61 0.311 0.291 0.2641 0.235 1.10 0.89
## ChOCI_R_P_2_PRE 61 0.377 0.424 0.4084 0.317 0.93 0.73
## ChOCI_R_P_3_PRE 61 0.137 0.175 0.1491 0.072 1.11 0.71
## ChOCI_R_P_4_PRE 61 0.423 0.436 0.4267 0.367 0.95 0.72
## ChOCI_R_P_5_PRE 61 0.181 0.221 0.2071 0.120 0.44 0.67
## ChOCI_R_P_6_PRE 61 0.394 0.399 0.3758 0.327 0.98 0.83
## ChOCI_R_P_7_PRE 61 0.229 0.291 0.2634 0.172 0.39 0.64
## ChOCI_R_P_8_PRE 61 0.356 0.379 0.3510 0.300 0.41 0.67
## ChOCI_R_P_9_PRE 61 0.175 0.240 0.2146 0.112 0.51 0.70
## ChOCI_R_P_10_PRE 61 0.526 0.551 0.5444 0.475 0.89 0.73
## ChOCI_R_P_12_PRE 61 0.590 0.575 0.5699 0.550 2.03 0.63
## ChOCI_R_P_13_PRE 61 0.646 0.581 0.5853 0.579 1.89 1.13
## ChOCI_R_P_14_PRE 61 0.603 0.556 0.5508 0.542 2.64 0.95
## ChOCI_R_P_15_PRE 61 0.381 0.341 0.3324 0.294 2.54 1.04
## ChOCI_R_P_16_PRE 61 0.599 0.561 0.5579 0.545 2.44 0.85
## ChOCI_R_P_17_PRE 61 0.638 0.579 0.5872 0.574 1.72 1.07
## ChOCI_R_P_18_PRE 61 0.259 0.325 0.3101 0.200 0.56 0.67
## ChOCI_R_P_19_PRE 61 0.462 0.473 0.4561 0.409 0.52 0.70
## ChOCI_R_P_20_PRE 61 0.347 0.400 0.3945 0.289 0.56 0.70
## ChOCI_R_P_21_PRE 61 0.340 0.366 0.3522 0.279 0.98 0.72
## ChOCI_R_P_22_PRE 61 0.250 0.314 0.3016 0.191 0.36 0.66
## ChOCI_R_P_23_PRE 61 0.347 0.414 0.3961 0.317 0.15 0.36
## ChOCI_R_P_24_PRE 61 0.296 0.364 0.3475 0.267 0.13 0.34
## ChOCI_R_P_25_PRE 61 0.171 0.227 0.2136 0.115 0.59 0.62
## ChOCI_R_P_26_PRE- 61 0.061 0.034 0.0049 0.020 3.85 0.44
## ChOCI_R_P_27_PRE 61 0.169 0.246 0.2229 0.132 0.16 0.42
## ChOCI_R_P_29_PRE 61 0.571 0.541 0.5417 0.505 1.89 0.98
## ChOCI_R_P_30_PRE 61 0.705 0.635 0.6425 0.646 1.59 1.13
## ChOCI_R_P_31_PRE 61 0.643 0.605 0.6045 0.583 2.25 1.01
## ChOCI_R_P_32_PRE 61 0.427 0.358 0.3549 0.343 2.13 1.06
## ChOCI_R_P_33_PRE 61 0.537 0.478 0.4814 0.468 2.54 0.98
## ChOCI_R_P_34_PRE 61 0.717 0.662 0.6705 0.666 1.57 1.02
##
## Non missing response frequency for each item
## 0 1 2 3 4 miss
## ChOCI_R_P_1_PRE 0.34 0.21 0.44 0.00 0.00 0
## ChOCI_R_P_2_PRE 0.30 0.48 0.23 0.00 0.00 0
## ChOCI_R_P_3_PRE 0.20 0.49 0.31 0.00 0.00 0
## ChOCI_R_P_4_PRE 0.28 0.49 0.23 0.00 0.00 0
## ChOCI_R_P_5_PRE 0.66 0.25 0.10 0.00 0.00 0
## ChOCI_R_P_6_PRE 0.34 0.33 0.33 0.00 0.00 0
## ChOCI_R_P_7_PRE 0.69 0.23 0.08 0.00 0.00 0
## ChOCI_R_P_8_PRE 0.69 0.21 0.10 0.00 0.00 0
## ChOCI_R_P_9_PRE 0.61 0.28 0.11 0.00 0.00 0
## ChOCI_R_P_10_PRE 0.33 0.46 0.21 0.00 0.00 0
## ChOCI_R_P_12_PRE 0.00 0.16 0.66 0.16 0.02 0
## ChOCI_R_P_13_PRE 0.13 0.21 0.38 0.20 0.08 0
## ChOCI_R_P_14_PRE 0.07 0.02 0.25 0.56 0.11 0
## ChOCI_R_P_15_PRE 0.05 0.05 0.43 0.26 0.21 0
## ChOCI_R_P_16_PRE 0.00 0.11 0.44 0.33 0.11 0
## ChOCI_R_P_17_PRE 0.18 0.20 0.34 0.28 0.00 0
## ChOCI_R_P_18_PRE 0.54 0.36 0.10 0.00 0.00 0
## ChOCI_R_P_19_PRE 0.59 0.30 0.11 0.00 0.00 0
## ChOCI_R_P_20_PRE 0.56 0.33 0.11 0.00 0.00 0
## ChOCI_R_P_21_PRE 0.26 0.49 0.25 0.00 0.00 0
## ChOCI_R_P_22_PRE 0.74 0.16 0.10 0.00 0.00 0
## ChOCI_R_P_23_PRE 0.85 0.15 0.00 0.00 0.00 0
## ChOCI_R_P_24_PRE 0.87 0.13 0.00 0.00 0.00 0
## ChOCI_R_P_25_PRE 0.48 0.46 0.07 0.00 0.00 0
## ChOCI_R_P_26_PRE 0.89 0.08 0.03 0.00 0.00 0
## ChOCI_R_P_27_PRE 0.85 0.13 0.02 0.00 0.00 0
## ChOCI_R_P_29_PRE 0.08 0.23 0.48 0.15 0.07 0
## ChOCI_R_P_30_PRE 0.21 0.25 0.31 0.20 0.03 0
## ChOCI_R_P_31_PRE 0.07 0.16 0.28 0.44 0.05 0
## ChOCI_R_P_32_PRE 0.08 0.15 0.43 0.25 0.10 0
## ChOCI_R_P_33_PRE 0.05 0.07 0.31 0.44 0.13 0
## ChOCI_R_P_34_PRE 0.20 0.23 0.38 0.20 0.00 0
##
## Reliability analysis
## Call: psych::alpha(x = data.frame(cybocs_items), check.keys = TRUE)
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd
## 0.48 0.71 0.7 0.33 2.4 0.082 8 1.9
##
## lower alpha upper 95% confidence boundaries
## 0.32 0.48 0.64
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N alpha se
## CYBOCS_pre_OBS 0.36 0.63 0.58 0.30 1.7 0.077
## CYBOCS_pre_COMP 0.30 0.59 0.53 0.26 1.4 0.092
## CYBOCS_pre_insight 0.47 0.70 0.68 0.37 2.3 0.088
## CYBOCS_pre_avoid 0.43 0.65 0.64 0.32 1.9 0.093
## CYBOCS_3m 0.69 0.72 0.68 0.39 2.6 0.045
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## CYBOCS_pre_OBS 61 0.54 0.73 0.68 0.39 11.0 2.40
## CYBOCS_pre_COMP 61 0.60 0.80 0.78 0.53 11.6 2.22
## CYBOCS_pre_insight 59 0.37 0.61 0.44 0.29 1.7 0.79
## CYBOCS_pre_avoid 55 0.50 0.69 0.56 0.47 1.6 0.95
## CYBOCS_3m 56 0.81 0.57 0.39 0.30 13.5 6.32
Alpha is at borderline (low). CYBOCS_3m appears to misfit. Maybe it is a dependent variable??? That would explain the result.
##
## Reliability analysis
## Call: psych::alpha(x = data.frame(EWSASC_items))
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd
## 0.86 0.86 0.88 0.55 6.2 0.028 3 1.9
##
## lower alpha upper 95% confidence boundaries
## 0.81 0.86 0.92
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N
## EWSASC_schoolandwork_PRE 0.87 0.87 0.89 0.63 6.9
## EWSASC_everydaysituations_PRE 0.88 0.87 0.89 0.62 6.7
## EWSASC_social_PRE 0.78 0.78 0.76 0.47 3.6
## EWSASC_leisuretime_PRE 0.79 0.78 0.76 0.48 3.6
## EWSASC_family_PRE 0.83 0.83 0.85 0.55 4.9
## alpha se
## EWSASC_schoolandwork_PRE 0.028
## EWSASC_everydaysituations_PRE 0.026
## EWSASC_social_PRE 0.045
## EWSASC_leisuretime_PRE 0.045
## EWSASC_family_PRE 0.035
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## EWSASC_schoolandwork_PRE 61 0.67 0.68 0.54 0.51 3.4 2.1
## EWSASC_everydaysituations_PRE 61 0.70 0.69 0.55 0.52 3.5 2.5
## EWSASC_social_PRE 61 0.92 0.92 0.97 0.87 2.6 2.5
## EWSASC_leisuretime_PRE 61 0.92 0.91 0.96 0.86 2.6 2.5
## EWSASC_family_PRE 61 0.80 0.80 0.73 0.68 2.7 2.2
##
## Non missing response frequency for each item
## 0 1 2 3 4 5 6 7 8
## EWSASC_schoolandwork_PRE 0.05 0.10 0.26 0.20 0.13 0.07 0.07 0.10 0.03
## EWSASC_everydaysituations_PRE 0.16 0.08 0.18 0.05 0.15 0.05 0.23 0.07 0.03
## EWSASC_social_PRE 0.28 0.15 0.15 0.11 0.07 0.08 0.07 0.07 0.03
## EWSASC_leisuretime_PRE 0.28 0.16 0.13 0.11 0.07 0.07 0.07 0.08 0.03
## EWSASC_family_PRE 0.20 0.16 0.16 0.15 0.13 0.07 0.07 0.05 0.02
## miss
## EWSASC_schoolandwork_PRE 0
## EWSASC_everydaysituations_PRE 0
## EWSASC_social_PRE 0
## EWSASC_leisuretime_PRE 0
## EWSASC_family_PRE 0
Good.
##
## Reliability analysis
## Call: psych::alpha(x = data.frame(SCAS_items))
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd
## 0.86 0.87 0.93 0.21 6.5 0.025 0.99 0.44
##
## lower alpha upper 95% confidence boundaries
## 0.81 0.86 0.91
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N alpha se
## SCAS_S_C_1_PRE 0.86 0.86 0.93 0.22 6.4 0.026
## SCAS_S_C_2_PRE 0.86 0.86 0.92 0.21 6.1 0.027
## SCAS_S_C_3_PRE 0.86 0.86 0.93 0.21 6.2 0.027
## SCAS_S_C_4_PRE 0.85 0.86 0.92 0.21 6.1 0.027
## SCAS_S_C_5_PRE 0.86 0.86 0.93 0.21 6.2 0.026
## SCAS_S_C_6_PRE 0.86 0.86 0.93 0.21 6.2 0.027
## SCAS_S_C_7_PRE 0.86 0.86 0.93 0.21 6.2 0.027
## SCAS_S_C_8_PRE 0.86 0.86 0.93 0.22 6.3 0.026
## SCAS_S_C_9_PRE 0.86 0.86 0.93 0.21 6.2 0.027
## SCAS_S_C_10_PRE 0.86 0.86 0.92 0.21 6.1 0.027
## SCAS_S_C_11_PRE 0.86 0.87 0.93 0.22 6.5 0.026
## SCAS_S_C_12_PRE 0.86 0.87 0.93 0.22 6.5 0.025
## SCAS_S_P_1_PRE 0.86 0.86 0.92 0.21 6.2 0.027
## SCAS_S_P_2_PRE 0.86 0.86 0.93 0.21 6.2 0.027
## SCAS_S_P_3_PRE 0.86 0.86 0.92 0.21 6.3 0.027
## SCAS_S_P_4_PRE 0.86 0.87 0.93 0.22 6.5 0.026
## SCAS_S_P_5_PRE 0.86 0.86 0.93 0.22 6.3 0.026
## SCAS_S_P_6_PRE 0.86 0.86 0.93 0.21 6.2 0.027
## SCAS_S_P_7_PRE 0.86 0.86 0.93 0.21 6.2 0.027
## SCAS_S_P_8_PRE 0.86 0.86 0.92 0.21 6.2 0.027
## SCAS_S_P_9_PRE 0.86 0.86 0.93 0.21 6.3 0.026
## SCAS_S_P_10_PRE 0.85 0.86 0.92 0.20 5.9 0.028
## SCAS_S_P_11_PRE 0.86 0.86 0.93 0.22 6.3 0.026
## SCAS_S_P_12_PRE 0.86 0.87 0.93 0.22 6.6 0.025
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## SCAS_S_C_1_PRE 61 0.43 0.42 0.41 0.36 1.03 0.91
## SCAS_S_C_2_PRE 61 0.57 0.58 0.57 0.51 0.85 0.83
## SCAS_S_C_3_PRE 61 0.56 0.55 0.54 0.50 1.57 0.96
## SCAS_S_C_4_PRE 61 0.58 0.59 0.57 0.53 0.54 0.79
## SCAS_S_C_5_PRE 61 0.50 0.51 0.49 0.43 1.02 0.94
## SCAS_S_C_6_PRE 61 0.51 0.51 0.49 0.45 1.59 0.88
## SCAS_S_C_7_PRE 61 0.52 0.52 0.50 0.46 0.79 0.90
## SCAS_S_C_8_PRE 61 0.48 0.47 0.45 0.40 1.56 1.01
## SCAS_S_C_9_PRE 61 0.53 0.54 0.53 0.47 0.56 0.87
## SCAS_S_C_10_PRE 61 0.57 0.57 0.57 0.50 0.64 0.91
## SCAS_S_C_11_PRE 61 0.39 0.38 0.33 0.31 1.16 0.97
## SCAS_S_C_12_PRE 61 0.38 0.37 0.34 0.29 1.26 1.06
## SCAS_S_P_1_PRE 61 0.51 0.51 0.50 0.44 0.87 0.94
## SCAS_S_P_2_PRE 61 0.52 0.52 0.51 0.46 0.82 0.85
## SCAS_S_P_3_PRE 61 0.51 0.50 0.50 0.44 1.52 0.98
## SCAS_S_P_4_PRE 61 0.37 0.37 0.35 0.29 0.56 0.94
## SCAS_S_P_5_PRE 61 0.47 0.48 0.44 0.40 0.93 0.85
## SCAS_S_P_6_PRE 61 0.55 0.55 0.54 0.49 1.54 0.91
## SCAS_S_P_7_PRE 61 0.53 0.54 0.52 0.46 0.61 0.90
## SCAS_S_P_8_PRE 61 0.52 0.51 0.51 0.45 1.26 1.03
## SCAS_S_P_9_PRE 61 0.46 0.48 0.46 0.41 0.34 0.57
## SCAS_S_P_10_PRE 61 0.68 0.70 0.69 0.64 0.44 0.74
## SCAS_S_P_11_PRE 61 0.45 0.46 0.43 0.38 0.89 0.91
## SCAS_S_P_12_PRE 61 0.29 0.29 0.25 0.21 1.30 0.90
##
## Non missing response frequency for each item
## 0 1 2 3 miss
## SCAS_S_C_1_PRE 0.28 0.52 0.08 0.11 0
## SCAS_S_C_2_PRE 0.39 0.39 0.18 0.03 0
## SCAS_S_C_3_PRE 0.15 0.31 0.36 0.18 0
## SCAS_S_C_4_PRE 0.61 0.28 0.08 0.03 0
## SCAS_S_C_5_PRE 0.34 0.38 0.20 0.08 0
## SCAS_S_C_6_PRE 0.10 0.38 0.36 0.16 0
## SCAS_S_C_7_PRE 0.48 0.31 0.16 0.05 0
## SCAS_S_C_8_PRE 0.15 0.38 0.25 0.23 0
## SCAS_S_C_9_PRE 0.66 0.16 0.15 0.03 0
## SCAS_S_C_10_PRE 0.61 0.20 0.15 0.05 0
## SCAS_S_C_11_PRE 0.30 0.34 0.26 0.10 0
## SCAS_S_C_12_PRE 0.30 0.31 0.23 0.16 0
## SCAS_S_P_1_PRE 0.41 0.41 0.08 0.10 0
## SCAS_S_P_2_PRE 0.39 0.46 0.08 0.07 0
## SCAS_S_P_3_PRE 0.15 0.38 0.28 0.20 0
## SCAS_S_P_4_PRE 0.67 0.18 0.07 0.08 0
## SCAS_S_P_5_PRE 0.34 0.43 0.18 0.05 0
## SCAS_S_P_6_PRE 0.11 0.39 0.33 0.16 0
## SCAS_S_P_7_PRE 0.62 0.20 0.13 0.05 0
## SCAS_S_P_8_PRE 0.28 0.33 0.25 0.15 0
## SCAS_S_P_9_PRE 0.70 0.25 0.05 0.00 0
## SCAS_S_P_10_PRE 0.69 0.20 0.10 0.02 0
## SCAS_S_P_11_PRE 0.44 0.26 0.26 0.03 0
## SCAS_S_P_12_PRE 0.23 0.31 0.39 0.07 0
##
## Reliability analysis
## Call: psych::alpha(x = data.frame(CDI_items))
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd
## 0.81 0.81 0.86 0.28 4.2 0.035 0.4 0.31
##
## lower alpha upper 95% confidence boundaries
## 0.74 0.81 0.88
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N alpha se
## PanicDisorder 0.82 0.82 0.85 0.32 4.7 0.035
## CDI_S_1_PRE 0.79 0.78 0.83 0.26 3.6 0.039
## CDI_S_2_PRE 0.78 0.78 0.83 0.27 3.6 0.040
## CDI_S_3_PRE 0.80 0.80 0.84 0.28 3.9 0.037
## CDI_S_4_PRE 0.77 0.77 0.81 0.25 3.3 0.041
## CDI_S_5_PRE 0.79 0.79 0.83 0.27 3.8 0.038
## CDI_S_6_PRE 0.80 0.79 0.84 0.28 3.8 0.037
## CDI_S_7_PRE 0.79 0.79 0.84 0.27 3.7 0.039
## CDI_S_8_PRE 0.78 0.79 0.83 0.27 3.7 0.039
## CDI_S_9_PRE 0.80 0.80 0.85 0.29 4.1 0.036
## CDI_S_10_PRE 0.79 0.79 0.84 0.27 3.8 0.038
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## PanicDisorder 61 0.21 0.29 0.20 0.13 0.082 0.28
## CDI_S_1_PRE 61 0.64 0.67 0.64 0.54 0.328 0.51
## CDI_S_2_PRE 61 0.67 0.65 0.61 0.55 0.492 0.62
## CDI_S_3_PRE 61 0.52 0.55 0.49 0.41 0.393 0.49
## CDI_S_4_PRE 61 0.75 0.76 0.77 0.69 0.262 0.44
## CDI_S_5_PRE 61 0.59 0.59 0.56 0.49 0.197 0.44
## CDI_S_6_PRE 61 0.62 0.59 0.53 0.47 0.885 0.71
## CDI_S_7_PRE 61 0.64 0.62 0.55 0.52 0.623 0.58
## CDI_S_8_PRE 61 0.66 0.64 0.62 0.54 0.492 0.62
## CDI_S_9_PRE 61 0.51 0.49 0.42 0.37 0.508 0.57
## CDI_S_10_PRE 61 0.57 0.60 0.56 0.48 0.164 0.42
##
## Non missing response frequency for each item
## 0 1 2 miss
## PanicDisorder 0.92 0.08 0.00 0
## CDI_S_1_PRE 0.69 0.30 0.02 0
## CDI_S_2_PRE 0.57 0.36 0.07 0
## CDI_S_3_PRE 0.61 0.39 0.00 0
## CDI_S_4_PRE 0.74 0.26 0.00 0
## CDI_S_5_PRE 0.82 0.16 0.02 0
## CDI_S_6_PRE 0.31 0.49 0.20 0
## CDI_S_7_PRE 0.43 0.52 0.05 0
## CDI_S_8_PRE 0.57 0.36 0.07 0
## CDI_S_9_PRE 0.52 0.44 0.03 0
## CDI_S_10_PRE 0.85 0.13 0.02 0
##
## Reliability analysis
## Call: psych::alpha(x = data.frame(FAS_items))
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd
## 0.91 0.92 0.94 0.48 11 0.016 1.4 0.95
##
## lower alpha upper 95% confidence boundaries
## 0.88 0.91 0.95
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N alpha se
## FAS_PR_1_PRE 0.91 0.92 0.94 0.50 11.0 0.017
## FAS_PR_2_PRE 0.90 0.91 0.93 0.47 9.6 0.019
## FAS_PR_3_PRE 0.91 0.91 0.94 0.49 10.5 0.017
## FAS_PR_4_PRE 0.91 0.91 0.94 0.49 10.7 0.017
## FAS_PR_5_PRE 0.91 0.91 0.93 0.48 10.1 0.017
## FAS_PR_6_PRE 0.91 0.91 0.93 0.47 9.8 0.018
## FAS_PR_7_PRE 0.91 0.91 0.93 0.47 9.9 0.018
## FAS_PR_8_PRE 0.91 0.91 0.93 0.48 10.1 0.017
## FAS_PR_9_PRE 0.90 0.91 0.93 0.47 9.8 0.018
## FAS_PR_10_PRE 0.91 0.91 0.93 0.48 10.1 0.018
## FAS_PR_11_PRE 0.91 0.91 0.93 0.48 10.1 0.017
## FAS_PR_12_PRE 0.91 0.91 0.94 0.48 10.0 0.018
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## FAS_PR_1_PRE 61 0.59 0.60 0.54 0.52 2.89 1.1
## FAS_PR_2_PRE 61 0.82 0.81 0.79 0.77 1.30 1.6
## FAS_PR_3_PRE 61 0.69 0.67 0.63 0.60 1.93 1.7
## FAS_PR_4_PRE 61 0.64 0.63 0.59 0.56 1.77 1.4
## FAS_PR_5_PRE 61 0.71 0.73 0.70 0.66 0.64 1.0
## FAS_PR_6_PRE 61 0.76 0.77 0.76 0.71 1.28 1.3
## FAS_PR_7_PRE 61 0.76 0.76 0.74 0.70 1.28 1.3
## FAS_PR_8_PRE 61 0.72 0.73 0.73 0.66 0.87 1.3
## FAS_PR_9_PRE 61 0.77 0.78 0.78 0.72 0.79 1.3
## FAS_PR_10_PRE 61 0.73 0.73 0.72 0.67 1.28 1.2
## FAS_PR_11_PRE 61 0.73 0.73 0.72 0.67 1.25 1.3
## FAS_PR_12_PRE 61 0.74 0.75 0.71 0.68 1.25 1.3
##
## Non missing response frequency for each item
## 0 1 2 3 4 miss
## FAS_PR_1_PRE 0.03 0.08 0.26 0.21 0.41 0
## FAS_PR_2_PRE 0.51 0.13 0.08 0.11 0.16 0
## FAS_PR_3_PRE 0.28 0.21 0.13 0.05 0.33 0
## FAS_PR_4_PRE 0.23 0.30 0.13 0.16 0.18 0
## FAS_PR_5_PRE 0.61 0.28 0.02 0.07 0.03 0
## FAS_PR_6_PRE 0.38 0.23 0.20 0.13 0.07 0
## FAS_PR_7_PRE 0.43 0.10 0.26 0.20 0.02 0
## FAS_PR_8_PRE 0.61 0.11 0.13 0.10 0.05 0
## FAS_PR_9_PRE 0.67 0.08 0.08 0.11 0.05 0
## FAS_PR_10_PRE 0.34 0.28 0.18 0.15 0.05 0
## FAS_PR_11_PRE 0.43 0.18 0.16 0.18 0.05 0
## FAS_PR_12_PRE 0.43 0.13 0.26 0.13 0.05 0
##
## Reliability analysis
## Call: psych::alpha(x = data.frame(EWSASP_items))
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd
## 0.8 0.8 0.8 0.45 4 0.041 3.1 1.8
##
## lower alpha upper 95% confidence boundaries
## 0.72 0.8 0.88
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N
## EWSASP_schoolandwork_PRE 0.78 0.78 0.74 0.46 3.4
## EWSASP_everydaysituations_PRE 0.75 0.75 0.72 0.43 3.0
## EWSASP_social_PRE 0.75 0.75 0.72 0.42 2.9
## EWSASP_leisuretime_PRE 0.77 0.77 0.76 0.46 3.4
## EWSASP_family_PRE 0.77 0.77 0.72 0.46 3.4
## alpha se
## EWSASP_schoolandwork_PRE 0.047
## EWSASP_everydaysituations_PRE 0.053
## EWSASP_social_PRE 0.053
## EWSASP_leisuretime_PRE 0.048
## EWSASP_family_PRE 0.048
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## EWSASP_schoolandwork_PRE 61 0.72 0.72 0.63 0.54 4.0 2.5
## EWSASP_everydaysituations_PRE 61 0.79 0.78 0.71 0.63 3.5 2.6
## EWSASP_social_PRE 61 0.78 0.78 0.72 0.64 2.8 2.4
## EWSASP_leisuretime_PRE 61 0.71 0.73 0.62 0.56 1.8 2.2
## EWSASP_family_PRE 61 0.72 0.72 0.66 0.55 3.4 2.4
##
## Non missing response frequency for each item
## 0 1 2 3 4 5 6 7 8
## EWSASP_schoolandwork_PRE 0.08 0.05 0.26 0.07 0.13 0.10 0.11 0.07 0.13
## EWSASP_everydaysituations_PRE 0.16 0.13 0.08 0.08 0.21 0.05 0.13 0.07 0.08
## EWSASP_social_PRE 0.23 0.13 0.21 0.10 0.07 0.05 0.15 0.02 0.05
## EWSASP_leisuretime_PRE 0.41 0.15 0.15 0.07 0.10 0.03 0.07 0.02 0.02
## EWSASP_family_PRE 0.18 0.08 0.10 0.16 0.15 0.08 0.16 0.05 0.03
## miss
## EWSASP_schoolandwork_PRE 0
## EWSASP_everydaysituations_PRE 0
## EWSASP_social_PRE 0
## EWSASP_leisuretime_PRE 0
## EWSASP_family_PRE 0
The (non-nzv) comorbities are: Depression, PanicDisorder, SocialPhob, SpecificPhob, TourettesTics, ADHD, GAD, responder_3m_f. The Odds ratios of the comorbities with the outcome variable are: 1.48, 2.33, 0.95, 4.31, 0.45, 0.25, 1.5, 0. The odds are computed in favor of treatment success.
The relative risks of the comorbities with the outcome variable are: 0, 0.38, 0.59, 0.97, 1.24, 1.25, 1.53, 1.94. Relativs Risks are also computed in favor of success (so, they depict rather relative protectino probabilities).
Let’s plot the assocation of the comorbitity with the outcome var responder_3m. To that end, let’s tabulate the the 2x2 matrices (contingency matrices) for each comorbidity (yes/no) vs. responder (yes/no). For convenience, proportions (%) are depicted.
## [1] "Depression"
##
## 1 0
## 0 0.38 0.55
## 1 0.04 0.04
## [1] "PanicDisorder"
##
## 1 0
## 0 0.36 0.55
## 1 0.05 0.04
## [1] "SocialPhob"
##
## 1 0
## 0 0.38 0.54
## 1 0.04 0.05
## [1] "SpecificPhob"
##
## 1 0
## 0 0.32 0.55
## 1 0.09 0.04
## [1] "TourettesTics"
##
## 1 0
## 0 0.39 0.54
## 1 0.02 0.05
## [1] "ADHD"
##
## 1 0
## 0 0.39 0.50
## 1 0.02 0.09
## [1] "GAD"
##
## 1 0
## 0 0.36 0.54
## 1 0.05 0.05
## [1] "responder_3m"
##
## 1 0
## 0 0.00 0.59
## 1 0.41 0.00
## [1] "responder_3m_f"
##
## 1 0
## 1 0.41 0.00
## 0 0.00 0.59
Let’s divide that up for each comorbidity, and plot it:
Some differences in the joint distribution of comorbidities and response appear.
Quite a few NAs.
Let’s look at it from some other perspective, different code, and plot it again, and see what happens:
And what it about if we eyeball the plain number? The table shows the frequencies for treatment success/failure as a contigency of comorbidity.
| key | value | responder_3m | n |
|---|---|---|---|
| ADHD | 0 | 0 | 28 |
| ADHD | 0 | 1 | 22 |
| ADHD | 0 | NA | 5 |
| ADHD | 1 | 0 | 5 |
| ADHD | 1 | 1 | 1 |
| Agoraphobia | 0 | 0 | 33 |
| Agoraphobia | 0 | 1 | 23 |
| Agoraphobia | 0 | NA | 5 |
| Depression | 0 | 0 | 31 |
| Depression | 0 | 1 | 21 |
| Depression | 0 | NA | 4 |
| Depression | 1 | 0 | 2 |
| Depression | 1 | 1 | 2 |
| Depression | 1 | NA | 1 |
| Dystymia | 0 | 0 | 31 |
| Dystymia | 0 | 1 | 23 |
| Dystymia | 0 | NA | 5 |
| Dystymia | 1 | 0 | 2 |
| EatingDis | 0 | 0 | 33 |
| EatingDis | 0 | 1 | 23 |
| EatingDis | 0 | NA | 5 |
| GAD | 0 | 0 | 30 |
| GAD | 0 | 1 | 20 |
| GAD | 0 | NA | 3 |
| GAD | 1 | 0 | 3 |
| GAD | 1 | 1 | 3 |
| GAD | 1 | NA | 2 |
| ODD | 0 | 0 | 33 |
| ODD | 0 | 1 | 23 |
| ODD | 0 | NA | 5 |
| PanicDisorder | 0 | 0 | 31 |
| PanicDisorder | 0 | 1 | 20 |
| PanicDisorder | 0 | NA | 5 |
| PanicDisorder | 1 | 0 | 2 |
| PanicDisorder | 1 | 1 | 3 |
| PTSD | 0 | 0 | 33 |
| PTSD | 0 | 1 | 22 |
| PTSD | 0 | NA | 5 |
| PTSD | 1 | 1 | 1 |
| SeparationAnx | 0 | 0 | 33 |
| SeparationAnx | 0 | 1 | 23 |
| SeparationAnx | 0 | NA | 5 |
| SocialPhob | 0 | 0 | 30 |
| SocialPhob | 0 | 1 | 21 |
| SocialPhob | 0 | NA | 5 |
| SocialPhob | 1 | 0 | 3 |
| SocialPhob | 1 | 1 | 2 |
| SpecificPhob | 0 | 0 | 31 |
| SpecificPhob | 0 | 1 | 18 |
| SpecificPhob | 0 | NA | 5 |
| SpecificPhob | 1 | 0 | 2 |
| SpecificPhob | 1 | 1 | 5 |
| TourettesTics | 0 | 0 | 30 |
| TourettesTics | 0 | 1 | 22 |
| TourettesTics | 0 | NA | 5 |
| TourettesTics | 1 | 0 | 3 |
| TourettesTics | 1 | 1 | 1 |
Let’s see which predictor variables (of the sum scores) correlate most strongly with the outcome.
| Predictor | CYBOCS_3m |
|---|---|
| CYBOCS_3m | 1.00 |
| ChOCI_R_P_sumimp_PRE | 0.43 |
| EWSASP_sum_PRE | 0.43 |
| CDI_S_sum_PRE | 0.37 |
| SCAS_S_P_sum_PRE | 0.35 |
| FAS_PR_sum_PRE | 0.33 |
| ChOCI_R_C_sumimp_PRE | 0.31 |
| EWSASC_sum_PRE | 0.28 |
| CYBOCS_pre_sum | 0.26 |
| ChOCI_R_P_sumsym_PRE | 0.26 |
| ChOCI_R_C_sumsym_PRE | 0.09 |
| SCAS_S_C_sum_PRE | 0.07 |
Ok, that’s quite a range in strength of assocation.
Let’s visualize the correlations of the sumscores (of the psychometric scales) with the outcome variable.
Let’s focus on the most important variables, to make life easier.
That should be all sum scores. Let’s look for them:
Ok, the variables are CYBOCS_pre_sum, ChOCI_R_C_sumsym_PRE, ChOCI_R_C_sumimp_PRE, EWSASC_sum_PRE, SCAS_S_C_sum_PRE, CDI_S_sum_PRE, ChOCI_R_P_sumsym_PRE, ChOCI_R_P_sumimp_PRE, FAS_PR_sum_PRE, EWSASP_sum_PRE, SCAS_S_P_sum_PRE. In total, 11 variables.
We can probably safely ignore ID. We should include basic and demographic variables:
Which gives us group, sex, age, Birthcountry, Education_parent, OCDonset, yearswithOCD, contact, distance, medication, medication_yesno, treatm_exp, OCD_treatm_exp, responder_3m, CYBOCS_3m, another 15 variables.
Of particular interest are of course responder_3m, CYBOCS_3m (outcomes) and group (experimental factor).
Next, let’s name the comorbidities.
These are Depression, Dystymia, PanicDisorder, Agoraphobia, SeparationAnx, SocialPhob, SpecificPhob, PTSD, TourettesTics, ADHD, ODD, EatingDis, GAD.
In total, 3 sets of variables then: basic variables (including outcome and experimental variables), sum scores of psychometric battery, and comorbidity.
In total, 39 Variables: group, sex, age, Birthcountry, Education_parent, OCDonset, yearswithOCD, contact, distance, medication, medication_yesno, treatm_exp, OCD_treatm_exp, responder_3m, CYBOCS_3m, CYBOCS_pre_sum, ChOCI_R_C_sumsym_PRE, ChOCI_R_C_sumimp_PRE, EWSASC_sum_PRE, SCAS_S_C_sum_PRE, CDI_S_sum_PRE, ChOCI_R_P_sumsym_PRE, ChOCI_R_P_sumimp_PRE, FAS_PR_sum_PRE, EWSASP_sum_PRE, SCAS_S_P_sum_PRE, Depression, Dystymia, PanicDisorder, Agoraphobia, SeparationAnx, SocialPhob, SpecificPhob, PTSD, TourettesTics, ADHD, ODD, EatingDis, GAD.
Vague defined, the model can be described as consisting of these predictors: demographics, psychometric scales, treatment (group), comorbities. The outcome is treatment response.
When tallying up sum scores, missing values cause problems. Assume 10 items to summed up. What if I have not responded to 9 items? If you count “zero” for the missing values, you will dramatically underestimate my true score. I wonder how the sum scores have been built here.
The most items appear in the ChOCI scale. So let’s look there first.
Ok, good, no missings. Have they been replaced somehow? Where the participants forced to give some answer? This might be of interest for gauging the psychometric quality of the scale.
| item | n_na |
|---|---|
| CYBOCS_pre_OBS | 0 |
| CYBOCS_pre_COMP | 0 |
| CYBOCS_pre_sum | 0 |
| CYBOCS_pre_insight | 2 |
| CYBOCS_pre_avoid | 6 |
| CYBOCS_3m | 5 |
Hm, here we find some missing values. So what was done to prevent bias here? We should follow up on that.
Same procedure…
| item | n_na |
|---|---|
| EWSASC_schoolandwork_PRE | 0 |
| EWSASC_everydaysituations_PRE | 0 |
| EWSASC_social_PRE | 0 |
| EWSASC_leisuretime_PRE | 0 |
| EWSASC_family_PRE | 0 |
| EWSASC_sum_PRE | 0 |
Ok, no NA’s.
| item | n_na |
|---|---|
| SCAS_S_C_1_PRE | 0 |
| SCAS_S_C_2_PRE | 0 |
| SCAS_S_C_3_PRE | 0 |
| SCAS_S_C_4_PRE | 0 |
| SCAS_S_C_5_PRE | 0 |
| SCAS_S_C_6_PRE | 0 |
| SCAS_S_C_7_PRE | 0 |
| SCAS_S_C_8_PRE | 0 |
| SCAS_S_C_9_PRE | 0 |
| SCAS_S_C_10_PRE | 0 |
| SCAS_S_C_11_PRE | 0 |
| SCAS_S_C_12_PRE | 0 |
| SCAS_S_C_sum_PRE | 0 |
| SCAS_S_P_1_PRE | 0 |
| SCAS_S_P_2_PRE | 0 |
| SCAS_S_P_3_PRE | 0 |
| SCAS_S_P_4_PRE | 0 |
| SCAS_S_P_5_PRE | 0 |
| SCAS_S_P_6_PRE | 0 |
| SCAS_S_P_7_PRE | 0 |
| SCAS_S_P_8_PRE | 0 |
| SCAS_S_P_9_PRE | 0 |
| SCAS_S_P_10_PRE | 0 |
| SCAS_S_P_11_PRE | 0 |
| SCAS_S_P_12_PRE | 0 |
| SCAS_S_P_sum_PRE | 0 |
No NA’s.
| item | n_na |
|---|---|
| PanicDisorder | 0 |
| CDI_S_1_PRE | 0 |
| CDI_S_2_PRE | 0 |
| CDI_S_3_PRE | 0 |
| CDI_S_4_PRE | 0 |
| CDI_S_5_PRE | 0 |
| CDI_S_6_PRE | 0 |
| CDI_S_7_PRE | 0 |
| CDI_S_8_PRE | 0 |
| CDI_S_9_PRE | 0 |
| CDI_S_10_PRE | 0 |
| CDI_S_sum_PRE | 0 |
No NA’s.
| item | n_na |
|---|---|
| FAS_PR_1_PRE | 0 |
| FAS_PR_2_PRE | 0 |
| FAS_PR_3_PRE | 0 |
| FAS_PR_4_PRE | 0 |
| FAS_PR_5_PRE | 0 |
| FAS_PR_6_PRE | 0 |
| FAS_PR_7_PRE | 0 |
| FAS_PR_8_PRE | 0 |
| FAS_PR_9_PRE | 0 |
| FAS_PR_10_PRE | 0 |
| FAS_PR_11_PRE | 0 |
| FAS_PR_12_PRE | 0 |
| FAS_PR_sum_PRE | 0 |
No NA’s.
| item | n_na |
|---|---|
| EWSASP_schoolandwork_PRE | 0 |
| EWSASP_everydaysituations_PRE | 0 |
| EWSASP_social_PRE | 0 |
| EWSASP_leisuretime_PRE | 0 |
| EWSASP_family_PRE | 0 |
| EWSASP_sum_PRE | 0 |
No NA’s.
| item | n_na |
|---|---|
| SCAS_S_C_1_PRE | 0 |
| SCAS_S_C_2_PRE | 0 |
| SCAS_S_C_3_PRE | 0 |
| SCAS_S_C_4_PRE | 0 |
| SCAS_S_C_5_PRE | 0 |
| SCAS_S_C_6_PRE | 0 |
| SCAS_S_C_7_PRE | 0 |
| SCAS_S_C_8_PRE | 0 |
| SCAS_S_C_9_PRE | 0 |
| SCAS_S_C_10_PRE | 0 |
| SCAS_S_C_11_PRE | 0 |
| SCAS_S_C_12_PRE | 0 |
| SCAS_S_C_sum_PRE | 0 |
| SCAS_S_P_1_PRE | 0 |
| SCAS_S_P_2_PRE | 0 |
| SCAS_S_P_3_PRE | 0 |
| SCAS_S_P_4_PRE | 0 |
| SCAS_S_P_5_PRE | 0 |
| SCAS_S_P_6_PRE | 0 |
| SCAS_S_P_7_PRE | 0 |
| SCAS_S_P_8_PRE | 0 |
| SCAS_S_P_9_PRE | 0 |
| SCAS_S_P_10_PRE | 0 |
| SCAS_S_P_11_PRE | 0 |
| SCAS_S_P_12_PRE | 0 |
| SCAS_S_P_sum_PRE | 0 |
No NA’s.
Before applying some sophisticated (aka esoteric) models, let’s perform the intraocular trauma test for the data: let’s see whether the effect is so crisp that it hits us right between the eyes. That is., is there an association between group and response?
Because for the fun of it (and because the question if of particular interest), let’s plot from different point of views.
Stapled bars:
facetted bars:
proportion bars (stapled):
Hm, it appears as if the experimental group was less successful than the control group. That result might hit us between the eyes… But one would certainly hope for something the other way round.
The bare numbers:
| group | responder_3m | n |
|---|---|---|
| ICBT | 0 | 21 |
| ICBT | 1 | 10 |
| ICBT | NA | 2 |
| waitlist | 0 | 12 |
| waitlist | 1 | 13 |
| waitlist | NA | 3 |
For this outcome, it seems as if there was some (slight?) advantage for the treatment group. However, the overlap is substantial.
Here come the bare figures:
| group | group_mean | group_md | group_sd | group_IQR |
|---|---|---|---|---|
| ICBT | 14.22581 | 14 | 5.903161 | 7 |
| waitlist | 12.56000 | 12 | 6.807349 | 9 |